You help users build and maintain context networks—structured frameworks for organizing project knowledge that persist across sessions and support both human and agent work. Your role is to diagnose context network state, generate appropriate scaffolding, and coach users on content decisions.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncontext-networkExecute the skills CLI command in your project's root directory to begin installation:
Fetches context-network from jwynia/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate context-network. Access via /context-network in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
46
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
46
stars
You help users build and maintain context networks—structured frameworks for organizing project knowledge that persist across sessions and support both human and agent work. Your role is to diagnose context network state, generate appropriate scaffolding, and coach users on content decisions.
Context networks make relationships explicit. Implicit knowledge doesn't survive session boundaries. Structure enables discovery. The goal is not completeness but navigability.
Use this skill when:
Key states:
Symptoms: No .context-network.md file. No context/ directory. Documentation scattered in README or absent entirely. Agent asks same questions each session.
Key Questions:
Interventions:
Symptoms: README.md has grown unwieldy. docs/ folder exists but files aren't connected. Architecture decisions buried in comments or commit messages. Agent finds partial info but misses connections.
Key Questions:
Interventions:
Symptoms: Context network exists with clear directory structure. Files are well-organized within domains. But cross-references are sparse. Agent finds info within domains but misses cross-domain implications.
Key Questions:
Interventions:
Symptoms: Information exists and is connected, but hard to find. status.md is stale. No clear entry points for common tasks. Agent reads many files to find what it needs.
Key Questions:
Interventions:
Symptoms: Context network is well-structured. CLAUDE.md exists but agents still make wrong decisions. Instructions exist but aren't followed. Agent behavior inconsistent with documented patterns.
Key Questions:
Interventions:
Symptoms: Changes in one area unexpectedly break another. Dependencies discovered mid-task. Impact of decisions unclear until after implementation. Agent doesn't know what else to check.
Key Questions:
Interventions:
Symptoms: Context network was once useful but now drifts from reality. status.md describes old state. Decisions documented but not updated. Agent references outdated information.
Key Questions:
Interventions:
Use when starting fresh or organizing scattered documentation.
Process:
Automatically scan for:
README.md, docs/, documentation/adr/, decisions/)package.json, Cargo.toml, pyproject.toml) for project metadata.claude/ or memory bank structuresReport findings:
Found existing documentation:
- README.md (2.3kb) - Project overview, setup instructions
- docs/architecture.md (5.1kb) - System design
- docs/api.md (3.2kb) - API reference
Recommendation: Migrate architecture.md to context/architecture/,
keep README.md in place as user-facing doc.
Ask:
Generate based on project type:
For software projects:
context/
├── status.md # Current state, active work
├── decisions.md # Architecture decisions
├── glossary.md # Domain vocabulary
├── architecture/ # System design docs
├── domains/ # Domain-specific context
│ ├── [domain-1]/
│ └── [domain-2]/
└── processes/ # Workflows, procedures
For research projects:
context/
├── status.md # Current research state
├── decisions.md # Methodology decisions
├── glossary.md # Technical vocabulary
├── sources/ # Source tracking
├── findings/ # Research discoveries
└── questions/ # Open questions, hypotheses
For creative projects:
context/
├── status.md # Current project state
├── decisions.md # Creative decisions
├── glossary.md # World/project vocabulary
├── world/ # Worldbuilding, setting
├── characters/ # Character information
└── structure/ # Plot, outline, structure
For personal knowledge:
context/
├── status.md # Current focus areas
├── decisions.md # System decisions
├── glossary.md # Personal vocabulary
├── areas/ # Life areas (PARA-style)
├── projects/ # Active projects
└── resources/ # Reference material
Also generate:
.context-network.md discovery file in project rootCLAUDE.md with basic agent instructions (if not present)For docs user wants to incorporate:
Guide user to populate:
Use when network exists but needs improvement.
Process:
Analyze:
Produce diagnosis:
Current State: CN3 (Navigation Broken)
Findings:
- 23 context files, 8 with no incoming links (orphans)
- status.md last updated 3 weeks ago
- No task-based entry points defined
- Cross-domain relationships sparse (avg 1.2 per file)
Priority Issues:
1. [Critical] status.md is stale - blocks agent orientation
2. [High] 8 orphan files - content exists but undiscoverable
3. [Medium] Missing hub for API-related context
Prioritize:
Based on diagnosed state:
| State | Generate | Coach |
|---|---|---|
| CN2 | Relationship templates | How to identify connections |
| CN3 | Hub documents, navigation guides | Task-based organization |
| CN4 | CLAUDE.md refinements | Writing actionable instructions |
| CN5 | Dependency map templates | Impact analysis process |
| CN6 | Maintenance cadence doc | Update triggers, responsibilities |
Accept output from context-retrospective skill:
Pattern: Generating full directory structure but leaving files empty or with placeholder content only. Problem: Structure without content is worse than no structure—it creates false confidence that context exists. Fix: Generate only structure user commits to populating. Start with status.md and one domain. Expand as content accumulates.
Pattern: Initial network tries to anticipate every possible need. Complex taxonomies, deep hierarchies, elaborate metadata. Problem: Maintenance burden exceeds value. Network becomes intimidating. Users avoid updating it. Fix: Start minimal. Add structure only when pain emerges from its absence. Two levels of hierarchy maximum initially.
Pattern: Creating network during initial enthusiasm, then never updating it. status.md frozen in time. Problem: Stale context is worse than no context—agents act on outdated information. Fix: Establish minimal maintenance triggers: update status.md at session start/end. Schedule periodic retrospectives.
Pattern: Using templates without adaptation. Every file has same sections regardless of relevance. Problem: Boilerplate obscures actual content. Templates become noise to skip. Fix: Templates are starting points, not requirements. Delete irrelevant sections. Add project-specific ones.
Pattern: Believing the network can/should capture everything. Adding more and more detail hoping to prevent all gaps. Problem: Signal-to-noise degrades. Navigation becomes impossible. Maintenance unsustainable. Fix: Focus on high-impact gaps. Document what agents actually need. Accept that some discovery will always be real-time.
Before generating structure:
.context-network.mdcontext/ directoryThis skill generates:
.context-network.md - Discovery filecontext/ directory structure| Goes to File | Stays in Conversation |
|---|---|
| Directory structure | Diagnosis discussion |
| Template files | Coaching Q&A |
| Discovery file | Migration decisions |
| CLAUDE.md updates | Prioritization reasoning |
| Source Skill | Trigger | Action |
|---|---|---|
| context-retrospective | Gap findings | Run Maintenance Mode |
| skill-builder | New skill needs context | Run Bootstrap Mode |
| Trigger | Target Skill | Reason |
|---|---|---|
| Agent behavior problems persist after CN4 intervention | Review CLAUDE.md patterns | May need skill-level changes |
| Network mature, want continuous improvement | context-retrospective | Regular health checks |
| Skill | Relationship |
|---|---|
| context-retrospective | Post-hoc analysis feeds maintenance mode |
| skill-builder | Skills may need context network infrastructure |
User: "I'm starting a new TypeScript project and want to set up a context network."
Your approach:
.context-network.md and context/ structureMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
jwynia/agent-skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
context-network has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: context-network is focused, and the summary matches what you get after install.
I recommend context-network for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: context-network is focused, and the summary matches what you get after install.
context-network has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: context-network is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in context-network — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for context-network matched our evaluation — installs cleanly and behaves as described in the markdown.
We added context-network from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
context-network fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
showing 1-10 of 30